AFNI program: slow_surf_clustsim.py
Output of -help
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slow_surf_clustsim.py - generate a tcsh script to run clustsim on surface
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examples: ~1~
1. basic: give 3 required inputs, all else is default ~2~
While a blur of 4.0 is the default, it is included for clarity.
slow_surf_clustsim.py -save_script surf.clustsim \
-uvar spec_file sb23_lh_141_std.spec \
-uvar surf_vol sb23_SurfVol_aligned+orig \
-uvar blur 4.0 \
-uvar vol_mask mask_3mm+orig \
2. more advanced, but still based on EPI analysis ~2~
Specify p-values, blur size and number of iterations, along with the
script name and results directory, use 10000 iterations, instead of
the default 1000.
slow_surf_clustsim.py -save_script surf.clustsim \
-uvar spec_file sb23_lh_141_std.spec \
-uvar surf_vol sb23_SurfVol_aligned+orig \
-uvar vol_mask mask_3mm+orig \
-uvar pthr_list 0.05 0.01 0.002 0.001 0.0002 0.0001 \
-uvar blur 8.0 \
-uvar niter 10000 \
-save_script csim.10000 \
-uvar results_dir clust.results.10000
3. basic, but on the surface (so no vol_mask is provided) ~2~
slow_surf_clustsim.py -save_script surf.sim.3 \
-on_surface yes \
-uvar blur 3.0 \
-uvar spec_file sb23_lh_141_std.spec \
-uvar surf_vol sb23_SurfVol_aligned+orig
One can also add a surface mask via '-uvar surf_mask smask_lh.gii'.
Note: it is appropriate to use a volume mask on the same grid as the data to
be analyzed, which is to say either the EPI grid (for functional
analysis) or perhaps the anatomical grid (for anatomical analysis,
such as of thickness measures).
Note: the niter values should match between this program and
quick.alpha.vals.py.
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applying the results: ~1~
The result of processing should be one z.max.* file for each uncorrected
p-value input to the program (or each default). These files contain the
maximum cluster sizes (in mm^2), per z-score/p-value, and are named using
the corresponding p-value, e.g. z.max.area.0.001 corresponds to p=0.001.
To get the cluster size required for some uncorrected p-value, run
quick.alpha.vals.py on the z.max.area file corresponding to the desired
p-value, and note the cluster area required for the chosen corrected p.
For example, running this:
quick.alpha.vals.py -niter 1000 z.max.area.0.001
might show that a minimum cluster size of 113 mm^2 would correspond to a
corrected p=0.05.
Use of -niter should match that from slow_surf_clustsim.py.
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script outline: ~1~
set control variables
create and enter results directory
convert p-value list (pthr_list) to z-scores (zthr_list)
create dummy time series of length itersize
for each iter ( iteration list )
3dcalc: generate noise volume
3dVol2Surf: map noise to surface
SurfSmooth: blur to FWHM
for each index ( itersize list )
for each zthr ( zthr_list )
SurfClust: make clust file clust.out.$iter.$index.$zthr
extract lists of maximum areas
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terminal options: ~1~
-help : show this help
-hist : show module history
-show_default_cvars : list default control variables
-show_default_uvars : list default user variables
-show_valid_opts : list valid options
-ver : show current version
other options: ~1~
-on_surface yes/no : if yes, start from noise on the surface
(so no volume data is involved)
-print_script : print script to terminal
-save_script FILE : save script to given file
-uvar value ... : set the user variable
(use -show_default_uvars to see user vars)
-verb LEVEL : set the verbosity level
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R Reynolds June 2011
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Thu Oct 10 09:43:25 PM EDT 2024